Skip to main content
Glama
GrigoriLab

claude-mux-iterm

by GrigoriLab

list_messages

Retrieve messages sent to the current session from other Claude Code sessions. Optionally filter to show only unread messages, helping you stay updated on inter-session notifications.

Instructions

List messages received by this session.

Use this to see what other sessions have communicated to you.

Args: current_task_id: Your current task ID. unread_only: Only show messages not yet acknowledged.

Returns: List of messages with metadata.

Example: >>> list_messages("task-a", unread_only=True) ListMessagesResult(messages=[...], unread_count=3, ...)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unread_onlyNo
current_task_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesHuman-readable status message
messagesNo
unread_countNo
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains the return type and the unread_only flag, implicitly indicating a read operation, but does not explicitly state whether listing messages has side effects (e.g., marking them as read) or any other behavioral nuances.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with distinct sections for summary, usage, arguments, return value, and an example. It is concise without unnecessary repetition, and every section serves a clear purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description gives all necessary context: purpose, usage, parameter meanings, return format, and a concrete example. With an output schema available, the description doesn't need to detail return structure further, so the coverage is fully adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates fully by documenting each parameter in the Args section. current_task_id is explained as 'Your current task ID' and unread_only as 'Only show messages not yet acknowledged,' adding meaningful semantics beyond the schema's bare type definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states 'List messages received by this session' with a specific verb and resource. It clearly differentiates from siblings like send_message and acknowledge_message, making the tool's unique purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The sentence 'Use this to see what other sessions have communicated to you' provides direct guidance on when to use the tool. While it doesn't explicitly mention alternatives or exclusions, the use case is clear and logically distinct from sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/GrigoriLab/claude-mux-iterm'

If you have feedback or need assistance with the MCP directory API, please join our Discord server